An improved moth-flame optimization algorithm for support vector machine prediction of photovoltaic power generation

• Main Authors: Lin, Guo Qian, Li, Ling Ling, Tseng, Ming Lang, Liu, Han Min, Yuan, Dong Dong, Tan, Raymond Girard R.
• Format: text
• Published: Animo Repository 2020
• Subjects: Photovoltaic power generation; Support vector machines; Chemical Engineering; Energy Systems
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/4134
• Institution: De La Salle University

With the expansion of grid-connected solar power generation, the variability of photovoltaic power generation has become increasingly pronounced. Accurate photovoltaic output prediction is necessary to ensure power system stability. In this work, an inertia weighting strategy and the Cauchy mutation...